Create README.md

README.md

@@ -0,0 +1,59 @@
+---
+base_model: broadfield-dev/bert-small-ner-pii-tuned-12261022
+library_name: transformers
+tags:
+- onnx
+- transformers
+- optimum
+- onnxruntime
+- token-classification
+- int8
+- quantized
+- mobile
+language: en
+pipeline_tag: token-classification
+---
+
+# ONNX Export: broadfield-dev/bert-small-ner-pii-tuned-12261022
+
+This is a version of [broadfield-dev/bert-small-ner-pii-tuned-12261022](https://huggingface.co/broadfield-dev/bert-small-ner-pii-tuned-12261022) that has been converted to ONNX and optimized.
+
+## Model Details
+- **Base Model:** `broadfield-dev/bert-small-ner-pii-tuned-12261022`
+- **Task:** `token-classification`
+- **Opset Version:** `17`
+- **Optimization:** `INT8 - Optimized for Mobile (ARM64)`
+
+## Usage
+
+### Installation
+```bash
+pip install onnxruntime transformers
+```
+
+### Python Example
+```python
+
+from transformers import AutoTokenizer
+import onnxruntime as ort
+import numpy as np
+
+# 1. Load Tokenizer
+tokenizer = AutoTokenizer.from_pretrained("YOUR_USERNAME/bert-small-ner-pii-tuned-12261022-onnx")
+
+# 2. Load Model
+session = ort.InferenceSession("model.onnx")
+
+# 3. Preprocess
+text = "This is a test sentence."
+inputs = tokenizer(text, return_tensors="np")
+
+# 4. Inference
+outputs = session.run(None, dict(inputs))
+print(outputs[0])
+
+```
+
+## About this Export
+This model was exported using [Optimum](https://huggingface.co/docs/optimum/index) and `onnxruntime`. 
+It includes the `INT8 - Optimized for Mobile (ARM64)` quantization settings.